Category "sentiment-analysis"

Is there any way to solve re.sub issue?

sub() missing 1 required positional argument: 'string' def preprocess_text(sentence): #Remove punctuations and numbers sentence = re.sub('[^a-zA-Z]', '

Use the polarity distribution of word to detect the sentiment of new words

I have just started a project in NLP. Suppose I have a graph for each word that shows the polarity distribution of sentiments for that word in different sentenc

Does Fine-tunning Bert Model in multiple times with different dataset make it more accuracy?

i'm totally new in NLP and Bert Model. What im trying to do right now is Sentiment Analysis on Twitter Trending Hashtag ("neg", "neu", "pos") by using DistilBer

convert from sentiment labels confidence to score

as a beginner was checking for some sentiment analysis apis and found that google cloud returns a single sentiment value whereas aws returns 3 labels confidence

Predicting Sentiment of Raw Text using Trained BERT Model, Hugging Face

I'm predicting sentiment analysis of Tweets with positive, negative, and neutral classes. I've trained a BERT model using Hugging Face. Now I'd like to make pre